About the service
I work professionally in web scraping, and my core principle is that a crawler must work not just in a demo, but months after launch. Most parsers don't break on the first page—they break on the ten-thousandth: the site changes a class name, pagination turns into infinite scroll, and request limits start silently returning empty pages. I build in protection against these failures from the start — retries, request rate adjustment, checkpoints and monitoring, so a task that crashes at night resumes correctly and doesn't silently corrupt data. Whether you need a one-time export of several thousand records or a regular pipeline with daily updates, I treat a scraper as a program that needs maintenance, not as a disposable script.
My main tool is Python. For static and well-structured sites, I use Scrapy: it provides parallelism, middleware, and pipelines out of the box. For pages with heavy JavaScript, single-page applications, and everything hidden behind rendering and clicks, I use Playwright—controlling a real browser, handling authentication, and waiting for exactly the content I need. I handle the complex parts too: proxy and user-agent rotation, respecting limits, pagination and lazy loading, parsing malformed HTML and reverse-engineering private JSON APIs that many sites use under the hood—usually faster and more stable than parsing the rendered page.
What you get is not a folder of raw HTML, but a clean dataset in the format you need—CSV, JSON, Excel, or straight into a database. I normalize fields, remove duplicates, validate types, and document what each column means and how it was collected. I'm ready to discuss the legal and ethical side of a source beforehand and will honestly say if a site isn't worth the effort. If you already have a source, send a sample URL and the list of fields you need, and I'll assess the task accurately.
— Spiders in Scrapy for large-scale parallel crawling
— Playwright automation for JavaScript and authenticated pages
— Anti-bot bypass: proxy rotation, timing, headers, retries
— Pagination, infinite scroll, and hidden JSON-API extraction
— Clean exports to CSV, JSON, Excel, or database
— Regular schedulable scrapers with monitoring and alerts
My main tool is Python. For static and well-structured sites, I use Scrapy: it provides parallelism, middleware, and pipelines out of the box. For pages with heavy JavaScript, single-page applications, and everything hidden behind rendering and clicks, I use Playwright—controlling a real browser, handling authentication, and waiting for exactly the content I need. I handle the complex parts too: proxy and user-agent rotation, respecting limits, pagination and lazy loading, parsing malformed HTML and reverse-engineering private JSON APIs that many sites use under the hood—usually faster and more stable than parsing the rendered page.
What you get is not a folder of raw HTML, but a clean dataset in the format you need—CSV, JSON, Excel, or straight into a database. I normalize fields, remove duplicates, validate types, and document what each column means and how it was collected. I'm ready to discuss the legal and ethical side of a source beforehand and will honestly say if a site isn't worth the effort. If you already have a source, send a sample URL and the list of fields you need, and I'll assess the task accurately.
— Spiders in Scrapy for large-scale parallel crawling
— Playwright automation for JavaScript and authenticated pages
— Anti-bot bypass: proxy rotation, timing, headers, retries
— Pagination, infinite scroll, and hidden JSON-API extraction
— Clean exports to CSV, JSON, Excel, or database
— Regular schedulable scrapers with monitoring and alerts
